Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for removing distortions in an actual transmitted signal transmitted by a high power amplifier, said actual transmitted signal including bits, said method comprising: providing a model of the high power amplifier that generates a reproduced transmitted signal of the actual transmitted signal; defining a series of Volterra coefficients from the reproduced transmitted signal using a Volterra model; receiving the actual transmitted signal in a receiver; and processing the actual transmitted signal in an equalizer in the receiver to generate a digital signal including the bits, wherein processing the actual transmitted signal in the equalizer includes providing parallel soft interference cancellation of the actual transmitted signal that cancels both linear and non-linear interference for each symbol of interest in the actual transmitted signal, filtering the actual transmitted signal after the parallel soft interference cancellation using a minimum mean square error filter that employs the Volterra coefficients to provide equalizer coefficients, and using the equalizer coefficients to generate a new extrinsic log-likelihood ratio (LLR) of the bits in the actual transmitted signal.
A method for improving signal quality in satellite communication systems where a high-power amplifier introduces distortions. The method involves creating a model of the amplifier using Volterra coefficients. At the receiver, an equalizer processes the received signal to remove these distortions and extract the original data bits. The equalizer uses parallel soft interference cancellation to reduce both linear and non-linear interference for each symbol. After cancellation, a minimum mean square error (MMSE) filter, using the Volterra coefficients, further refines the signal. Finally, new log-likelihood ratios (LLRs) for the data bits are calculated based on the filtered signal, providing a cleaner signal for decoding.
2. The method according to claim 1 wherein processing the actual transmitted signal in an equalizer includes providing the new extrinsic LLR of the bits to an outer channel decoder that decodes the bits.
The method for signal distortion removal described previously where an equalizer processes a received signal from a high-power amplifier after modeling the amplifier with Volterra coefficients, includes sending the newly calculated log-likelihood ratios (LLRs) of the data bits from the equalizer to an outer channel decoder. This decoder then uses these LLRs to decode the original data bits, improving the accuracy of the recovered signal.
3. The method according to claim 2 wherein the outer channel decoder provides an a priori LLR of the bits as a feedback signal to the equalizer.
The method for signal distortion removal using an equalizer and an outer channel decoder, now uses the outer channel decoder to improve the equalizer’s performance. Specifically, the outer channel decoder provides an a priori LLR (prior knowledge of the bit probabilities) of the bits back to the equalizer as a feedback signal. This feedback allows the equalizer to make better decisions during the interference cancellation and filtering steps.
4. The method according to claim 3 wherein providing parallel soft interference cancellation of the actual transmitted signal includes using the a priori LLR of the bits and a symbol mean to subtract the interference.
In the iterative equalization method that uses a priori LLR feedback to improve signal quality, the parallel soft interference cancellation part of the equalizer uses this a priori LLR, along with a symbol mean value, to subtract interference from the signal. This more informed subtraction process results in a more accurate cancellation of both linear and non-linear interference, leading to a cleaner signal.
5. The method according to claim 2 wherein using the equalizer coefficients to generate a new extrinsic LLR of the bits includes generating an a posteriori LLR of the bits using the equalizer coefficients and subtracting the a priori LLR of the bits from the a posteriori LLR of the bits to generate the new extrinsic LLR of the bits.
The method that uses an equalizer to remove signal distortions, where the equalizer provides new LLRs to an outer channel decoder, generates a new extrinsic LLR of the bits by first calculating an a posteriori LLR (the probability of a bit after observing the received signal) using the equalizer coefficients. Then, the a priori LLR (prior bit probability) is subtracted from the a posteriori LLR to produce the new extrinsic LLR, which is then sent to the outer channel decoder for improved decoding.
6. The method according to claim 1 wherein filtering the actual transmitted signal after signal cancellation in the equalizer includes solving an optimization problem that identifies a series of filter taps.
In the equalizer for removing signal distortions in high-power amplifier systems, after the parallel soft interference cancellation, the minimum mean square error (MMSE) filtering involves finding the optimal filter settings. This is done by solving an optimization problem to determine the best series of filter taps which minimize the error between the original and the received signal.
7. The method according to claim 1 wherein using the equalizer coefficients to generate the new extrinsic LLR includes employing a Gaussian approximation of inter-symbol interference plus noise.
When generating new extrinsic log-likelihood ratios (LLRs) using the equalizer coefficients in the method to remove distortions, a Gaussian approximation is used to model the combined effect of inter-symbol interference and noise. This simplifies the LLR calculation while still providing a reasonably accurate representation of the signal characteristics.
8. The method according to claim 1 wherein the high power amplifier is a traveling-wave tube amplifier or a solid-state power amplifier.
The high power amplifier, which is being modeled and compensated for in the signal distortion removal method, can be either a traveling-wave tube amplifier (TWTA) or a solid-state power amplifier (SSPA). The method is applicable regardless of which type of amplifier is used in the system.
9. The method according to claim 1 wherein the actual transmitted signal is a satellite signal.
The signal being processed in the signal distortion removal method is a satellite signal. The method is specifically designed to address the distortions introduced by high-power amplifiers in satellite communication systems.
10. A method for removing distortions from a transmitted signal received by a receiver using an equalizer in the receiver, said transmitted signal including bits, said method comprising: receiving an a priori log-likelihood ratio (LLR) of the bits in the equalizer; providing parallel soft interference cancellation of the transmitted signal that cancels both linear and non-linear interference for each symbol of interest in the transmitted signal using the a priori LLR of the bits; filtering the transmitted signal after the soft interference cancellation using a minimum mean square error filter that employs a series of Volterra coefficients provided by a Volterra model to generate equalizer coefficients; generating an a posteriori LLR of the bits in the transmitted signal using the equalizer coefficients; and subtracting the a priori LLR of the bits from the a posteriori LLR of the bits to generate a new extrinsic LLR of the bits.
A method for removing distortions from a transmitted signal in a receiver, using an equalizer, comprises these steps: The equalizer receives a priori log-likelihood ratios (LLRs) of the data bits. It then performs parallel soft interference cancellation using these a priori LLRs, effectively removing both linear and non-linear interference. A minimum mean square error (MMSE) filter, using Volterra coefficients, filters the signal after cancellation to generate equalizer coefficients. Next, it generates a posteriori LLRs of the bits using the equalizer coefficients. Finally, a new extrinsic LLR of the bits is created by subtracting the a priori LLRs from the a posteriori LLRs.
11. The method according to claim 10 wherein providing parallel soft interference cancellation of the transmitted signal includes using the a priori LLR of the bits and a symbol mean to subtract the interference.
Within the method that uses an equalizer to remove signal distortions and uses parallel soft interference cancellation of a transmitted signal based on a priori LLRs, the soft interference cancellation is performed using the a priori LLRs of the bits combined with a symbol mean value to subtract the estimated interference. This provides a better estimate and subtraction of the linear and non-linear interferences.
12. The method according to claim 10 wherein filtering the transmitted signal after soft interference cancellation in the equalizer includes solving an optimization problem that identifies a series of filter taps.
In the method that uses an equalizer to remove signal distortions with parallel soft interference cancellation and filtering, the filtering process after signal cancellation in the equalizer includes solving an optimization problem. This optimization problem aims to identify a series of filter taps that minimize the error between the original signal and the processed signal, resulting in better signal quality.
13. The method according to claim 10 wherein using the equalizer coefficients to generate an a priori LLR includes employing a Gaussian approximation of inter-symbol interference plus noise.
Within the signal distortion removal method, generating an a posteriori LLR of the bits using equalizer coefficients is achieved using a Gaussian approximation. This Gaussian approximation simplifies the modeling of the inter-symbol interference and noise components in the signal, allowing for a computationally efficient LLR calculation.
14. The method according to claim 10 wherein receiving an a priori LLR of the bits in the equalizer includes receiving the a priori LLR of the bits from an outer channel decoder.
Within the signal distortion removal method with iterative equalization, the process of receiving an a priori LLR of the bits in the equalizer involves obtaining this LLR from an outer channel decoder. This decoder processes the output of the equalizer and provides feedback in the form of a priori LLRs to refine the equalization process.
15. The method according to claim 10 wherein the transmitted signal is transmitted from a traveling-wave tube amplifier or a solid-state power amplifier.
In the distortion removal method, the transmitted signal which is being processed originates from a traveling-wave tube amplifier (TWTA) or a solid-state power amplifier (SSPA). The method addresses signal distortions introduced by either of these amplifier types.
16. The method according to claim 10 wherein the transmitted signal is a satellite signal.
In the distortion removal method that uses an equalizer to clean up a signal, the transmitted signal being processed is a satellite signal. The method is specifically designed to improve the quality of signals transmitted via satellite communication channels, which are prone to distortions from high-power amplifiers.
17. A receiver receiving a transmitted signal from a high power amplifier, said transmitted signal including bits, said receiver comprising: an outer channel decoder decoding the bits in the transmitted signal and providing an a priori log-likelihood ratio (LLR) of the bits; and an equalizer receiving the transmitted signal, said equalizer including a parallel soft interference cancellation processor that cancels both linear and non-linear interference for each symbol of interest in the transmitted signal using the a priori LLR of the bits, said equalizer further including a minimum mean square error filter that receives the transmitted signal from the parallel soft interference cancellation processor and filters the transmitted signal using Volterra coefficients to provide equalizer coefficients, said equalizer further including an LLR processor that generates an a posteriori LLR of the bits in the transmitted signal using the equalizer coefficients and generates an extrinsic LLR of the bits by subtracting the a priori LLR of the bits from the a posteriori LLR of the bits.
A receiver for satellite communications comprises: an outer channel decoder that decodes data bits from a received signal and generates a priori log-likelihood ratios (LLRs) of the bits. An equalizer receives the signal and uses a parallel soft interference cancellation processor to remove linear and non-linear interference from each symbol using the a priori LLRs. A minimum mean square error (MMSE) filter further processes the signal using Volterra coefficients to generate equalizer coefficients. An LLR processor then calculates a posteriori LLRs using these coefficients and determines the extrinsic LLRs by subtracting the a priori LLRs from the a posteriori LLRs.
18. The receiver according to claim 17 wherein the parallel soft interference cancellation processor uses the a priori LLR of the bits and a symbol mean to subtract the interference.
In the satellite receiver, the parallel soft interference cancellation processor, which is part of the equalizer, reduces signal distortion by using the a priori LLRs of the bits, received from the outer channel decoder, together with a symbol mean value to subtract interference. This provides a more refined interference cancellation.
19. The receiver according to claim 17 wherein the minimum mean square error filter solves an optimization problem that identifies a series of filter taps.
In the satellite receiver, the minimum mean square error (MMSE) filter, uses an optimization problem. This optimization problem identifies a set of filter taps that optimize the filtering process, minimizing the error and improving the signal quality after interference cancellation.
20. The receiver according to claim 17 wherein the LLR processor employs a Gaussian approximation of inter-symbol interference plus noise to generate the a priori LLR.
The LLR processor generates the a priori LLR of bits in the equalizer by using a Gaussian approximation method. This simplifies the modeling of inter-symbol interference and noise components within the transmitted signal.
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August 12, 2014
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